In this video I do a quick install of TensorFlow 2.0 and show some of the code changes that are needed to upgrade to TensorFlow 2.0.
I took a quick look at TensorFlow 2.0 to see how many of the examples from my course (Applications of Deep Neural Networks) would get broken. Since I am using Keras, it was not too bad. In this video I do a quick install of TensorFlow 2.0 and show some of the code changes that are needed to upgrade to TensorFlow 2.0.
Commands referred to in the video:
conda install -y jupyter conda install -y scipy pip install --upgrade sklearn conda install -y pandas conda install -y pandas-datareader conda install -y matplotlib conda install -y pillow conda install -y upgrade requests conda install -y upgrade h5py conda install -y nb_conda
CPU pip install tensorflow==2.0.0-alpha0 GPU pip install tensorflow-gpu==2.0.0-alpha0
python -m ipykernel install --user --name tensorflow-2.0 --display-name "Python 3.6 (tensorflow-2.0)"
Keras vs Tensorflow - Learn the differences between Keras and Tensorflow on basis of Ease to use, Fast development,Functionality,flexibility,Performance etc
We will go over what is the difference between pytorch, tensorflow and keras in this video. Pytorch and Tensorflow are two most popular deep learning frameworks. Pytorch is by facebook and Tensorflow is by Google. Keras is not a full fledge deep learning framework, it is just a wrapper around Tensorflow that provides some convenient APIs.
Keras Tutorial - Learn Keras Introduction, installation, Keras Features, Applications of Keras, Keras Layers, Keras models and keras visualize training.
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In this video, we will learn how to create custom layers on TensorFlow using Keras API. For this tutorial, we are going to create a custom Dense layer by ext...